Once available only to scientists, today machine learning (ML) is open to a much broader audience of software architects and engineers. In fact, the practice of ML is so advanced that some algorithm results look like "black magic,” even to experienced practitioners.

Join us at the Google Munich office for our latest meet-up, “Machine Learning Design, Demystified” for free food, beer, and discussion on machine learning architecture.

Inspired by attribute-driven design (ADD) and Smart Decisions (a software architecture design game for big data), our speakers are excited to share a new version of the game focused on designing ML systems.

In this interactive session, you will learn about designing the architecture for ML systems via series of gamified interactive exercises. We will simulate state-of-the-art ML design systems by analyzing both business and technical requirements, selecting the best matching algorithms, and teaching how to validate early design decisions using rapid prototyping techniques.

Attendees are encouraged to think of an ML use case and bring it for discussion.

About the Speakers:

Serge Haziyev – SVP, Advanced Technology

Serge Haziyev works as a SVP, Advanced Technology at SoftServe, a digital authority that advises and provides at the cutting-edge of technology. Serge has more than 20 years of experience in various technology domains including: Big Data, AI, IoT, and Cloud Computing.

He is a co-author of Smart Decisions (a.k.a., architectural poker game) currently used by SEI CMU to teach students to design Big Data solutions. Also, Serge is an active contributor to the software community by sharing industry-best practices through scientific (and not-so-scientific) publications.

Serge's current activities at SoftServe include leading AI, Big Data, IoT, and R&D advanced technology services, as well as conducting educational workshops, sharing concepts, and providing practical input to emerging technologies.

Iurii Milovanov – Data Science Practice Leader

Iurii Milovanov is a Data Science Practice Leader with more than 10 years of experience in building enterprise-level AI, big data and advanced analytics solutions.

Iurii is a computer science expert with strong emphasis on cutting-edge technologies. His research interests include various aspects of modern, progressive IT, and state-of-the-art artificial intelligence, such as distributed and parallel computing, large-scale machine learning, natural language processing, computer vision, and speech recognition.

Iurii is actively contributing to various research and scientific communities, including his participation in the KarooGP project, a genetic programming suite used at LIGO Lab for detecting gravitational-waves; SIMOC, an interactive model of a scalable, human community located on a remote planet; and DRLearner project, the first open source implementation of Google’s Deep Reinforcement Learning (DQN) algorithm for playing ATARI games.

Agenda:

17:30 – Doors Open

18:00 – Speaker + Q&A

18:45 – Networking